FUZZY LOGIC

in mathematics, a form of logic based on the concept of the fuzzy set. Membership in fuzzy sets is expressed in probabilities or degrees of truth, i.e., as a continuum of values ranging from 0 to 1. Fuzzy logic and fuzzy sets were first described in the mid-1960s by Lotfi Zadeh. According to fuzzy-logic theorists, classical logic oversimplifies the concept of set membership by flatly including or excluding an individual, whereas fuzzy logic expresses the extent to which an individual pertains to a set. For example, under classical logic, theoretical tree x is a member of the set of tall trees; in contrast, under fuzzy logic, x pertains partly to the set of tall trees and can be described as fairly tall. As a form of data processing, fuzzy logic is employed by advanced electronic computer systems. In less complex information processors, the possibility that a particular event will occur is expressed as a certainty (either false or true) represented by the binary digits 0 or 1. Fuzzy-logic systems, in contrast, break down the chance of the occurrence into varying degrees of truthfulness or falsehood (e.g., will occur, probably will occur, might occur, might not occur, etc.). This allows the outcome of an event to be expressed as a probability. Moreover, as additional data is gathered, many fuzzy-logic systems are able to adjust continually the values assigned to different probabilities. Because some fuzzy-logic systems appear able to learn from their mistakes and mimic human thought processes, they are often considered a crude form of artificial intelligence. Fuzzy-logic systems were considered an experimental technology during the 1980s, but they achieved commercial application in the early 1990s. Advanced clothes-washing machines, for example, use fuzzy-logic systems to detect and adapt to patterns of water movement during a wash cycle. Other applications for fuzzy logic include expert systems, self-regulating industrial controls, and computerized speech and handwriting recognition programs.